PERANCANGAN APLIKASI DETEKSI DINI PENYAKIT PADA AYAM MELALUI KOTORAN UNTUK MENJAGA POTENSI PETERNAKAN AYAM

Abstract

The poultry farming industry faces persistent challenges due to the rapid spread of diseases, leading to significant economic losses. This issue underscores the need for early disease detection tools. The goal of this community service project is to develop a mobile application that employs AI-driven computer vision to analyze chicken droppings, specifically targeting the detection of Coccidiosis, Newcastle Disease, and Salmonella, while also assessing overall chicken health. The project uses machine learning methods for image classification, integrating these into a user-friendly application accessible to farmers. The results of the project are measurable; the application achieved an accuracy rate of 96,67% based on the results of evaluating disease detection from the dataset. This outcome demonstrates the tool's potential to significantly improve poultry health management and reduce economic losses in the industry.